Noninvasive biomarkers are urgently needed for early detection of breast cancer since the risk of recurrence, morbidity and mortality are closely related to disease stage at the time of primary surgery. In the past decade, many proteomics-based approaches were developed that utilize the protein profiling of human body fluids or identification of putative biomarkers to obtain more knowledge on the effects of cancer emergence and progression. Herein, we report on an analysis of proteins in the tear fluid from breast carcinoma patients and healthy women using a de novo proteomic approach and 25 mixed samples from each group. This study included 25 patients with primary invasive breast carcinoma and 25 age-matched healthy controls. We performed a MALDI-TOF-TOF-driven semi-quantitative comparison of tear protein levels in cancer (CA) and control (CTRL) using a de novo approach in pooled samples. Over 150 proteins in the tear fluid of CTRL and CA were identified. Using an in-house-developed algorithm we found more than 20 proteins distinctly upregulated or downregulated in the CTRL and CA groups. We identified several proteins that had modified expression in breast cancer patients. These proteins are involved in host immune system pathways (e.g., C1Q1 or S100A8) and different metabolic cascades (ALDH3A or TPI). Further validation of the results in an independent population combined with individual protein profiling of participants is needed to confirm the specificity of our findings and may lead to a better understanding of the pathological mechanism of breast cancer.
Abstract. Non-invasive biomarkers for early breast cancer detection are urgently needed, as the risk of recurrent morbidity and mortality is closely related to the stage of the disease at the time of primary surgery. Currently, there are no established clinical biomarkers for breast cancer. Evaluation of protein expression patterns in body fluids using proteomic technologies can be used to discover new biomarkers for the detection of breast cancer. The aim of this study was to identify a biomarker signature identifying primary non-metastatic breast cancer and healthy controls. We screened 91 serum samples including 45 breast cancer patients and 46 healthy women using a proteomic approach. We found 14 biomarkers whose combination detects breast cancer patients from non-cancer controls with a sensitivity of 89% and specificity of 67%. Five biomarkers were comparable with previously identified proteins from published data using similar approaches. This biomarker panel allows accurate discrimination between breast cancer and healthy individuals. In addition, it could distinguish subgroups of breast cancer based on patterns of several specific biomarkers. Further validation of biomarkers could potentially facilitate the early diagnosis of breast cancer as an aid to imaging diagnostics.
We describe herein the third case of primary leiomyosarcoma of the breast in a 62-year-old man. Preoperative clinical examination and cytology findings indicated a leiomyosarcoma of the breast. A modified radical mastectomy was performed. Immunohistochemical analysis subsequently confirmed a diagnosis of leiomyosarcoma. After a follow-up period of 24 months, the patient is still in good health with no evidence of locoregional recurrence or distant metastasis.
Background Ischemic heart disease (IHD) is the most common cause of death with an increasing frequency worldwide. It accounts for approximately 20% of all deaths in Europe and the United States of America. Approximately 1/3 of the IHD patients present with sudden cardiac death. The acute presentation of IHD myocardial infarction (MI) is a life-threatening, serious health problem, which causes substantially morbidity and mortality. It is well established that the onset of MI follows a circadian and seasonal periodicity. Seasonal variation regarding the incidence and the short-term mortality of acute MI was frequently reported, but data about sex-specific differences are sparse. Purpose Thus, our objectives were to investigate seasonal variations of myocardial infarction. Methods We analyzed the impact of seasons on incidence and in-hospital mortality of patients with acute MI in Germany from 2005 to 2015. We included all MI patients (ICD code I21) with an acute MI (, but not those MI patients with a recurrent event in the first 28 days after a previous MI (ICD code I22)), who were hospitalized in Germany between 2005 and 2015, in this analysis (source: RDC of the Federal Statistical Office and the Statistical Offices of the federal states, DRG Statistics 2005–2015, own calculations). Results The nationwide sample comprised 3,008,188 hospitalizations of patients with MI (2005–2015). The annual incidence was 334.7 per 100.000 population. Incidence inclined from 316.3 to 341.6 per 100.000 population per year (β 0.17 [0.10 to 0.24], P<0.001), while in-hospital mortality rate decreased from 14.1% to 11.3% (β −0.29 [−0.30 to −0.28, P<0.001). Overall, 377,028 (12.5%) patients died in-hospital. Seasonal variation of both incidence and in-hospital mortality were of substantial magnitude. Seasonal incidence (86.1 vs. 79.0 per 100.000 population per year, P<0.001) and in-hospital mortality (13.2% vs. 12.1%, P<0.001) were higher in the winter than in the summer saeson. Risk to die in winter was elevated (OR 1.080 (95% CI 1.069–1.091), P<0.001) compared to summer season independently of sex, age and comorbidities. Reperfusion treatment with drug eluting stents and coronary artery bypass graft were more often used in summer. We observed sex-specific differences regarding the seasonal variation of in-hospital mortality: males showed lowest mortality in summer, while females during fall. Low temperature dependency of mortality seems more pronounced in males. Conclusions Incidence of acute MI increased 2005–2015, while in-hospital mortality rate decreased. Seasonal variations of incidence and in-hospital mortality were of substantial magnitude with lowest incidence and lowest mortality in the summer season. Additionally, we observed sex-specific differences regarding the seasonal variation of the in-hospital mortality. Acknowledgement/Funding This study was supported by the German Federal Ministry of Education and Research (BMBF 01EO1503)
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